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\begin{document}

\begin{center}
	{\huge Financial Markets Microstructure: Course Plan}
\end{center}
\bigskip

This list outlines the plan for the course together with main readings for each topic. Additional readings will be assigned during lectures, whenever needed. The plan is subject to change.
\medskip

\paragraph{Part 0}: Overview
\begin{itemize}
	\item \textit{Week 1}: Introduction
	\begin{itemize}
		\item FPR chapters 0, 1
	\end{itemize}
	\item \textit{Week 2}: Liquidity
	\begin{itemize}
		\item FPR chapters 0, 2
	\end{itemize}
\end{itemize}

\medskip 
\paragraph{Part 1}: Setting up the models
\begin{itemize}
	\item \textit{Weeks 3 and 4}: Dealer models 1; {Glosten-Milgrom}, fixed trade size; Bayes' Rule; adverse selection, order costs and inventory risk ({Stoll})
	\begin{itemize}
		\item FPR chapter 3
	\end{itemize}
	\item \textit{Week 5}: Dealer models 2; {Kyle}, variable trade size; market depth; estimating liquidity determinants
	\begin{itemize}
		\item FPR chapters 4, 5
	\end{itemize}
	\item \textit{Weeks 6-7}: Limit order book; {Glosten}: static, random market order demand; market design; {Parlour}: dynamic, endogenous market order demand
	\begin{itemize}
		\item FPR chapter 6
	\end{itemize}
	\item \textit{Week 6}: Problem set 1 out, due week 8
\end{itemize}

\medskip
\paragraph{Part 2}: Applying the models; topics
\begin{itemize}
	\item \textit{Week 8}: Fragmentation costs, {modified Kyle model}; fragmentation benefits, {modified Glosten LOB model}
	\begin{itemize}
		\item FPR chapter 7
	\end{itemize}
	\item \textit{Week 9}: Transparency: search costs, {modified GM model} for order flow transparency
	\begin{itemize}
		\item FPR chapters 8
	\end{itemize}
	\item \textit{Week 10}: Liquidity risk and Illiquidity premia
	\begin{itemize}
		\item FPR chapter 9
	\end{itemize}
	\item \textit{Week 10}: Problem set 2 out, due week 12
	\item \textit{Week 11}: Liquidity and corporate policy; Digital markets
	\begin{itemize}
		\item FPR chapter 10
		\item Kirilenko, Andrei A., and Andrew W. Lo. “Moore’s Law versus Murphy’s Law: Algorithmic Trading and Its Discontents.” The Journal of Economic Perspectives 27, no. 2 (2013): 51–72. \url{https://dx.doi.org/10.1257/jep.27.2.51}
		\item Nica, Octavian, Karolina Piotrowska, and Klaus Reiner Schenk-Hoppé. “Cryptocurrencies: Economic Benefits and Risks.” SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, Oct 2017. \url{https://doi.org/10.2139/ssrn.3059856}
	\end{itemize}
	\item \textit{Week 12}: High-frequency trading
	\begin{itemize}
		\item Beason, Tyler, and Sunil Wahal. “The Anatomy of Trading Algorithms.” SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, December 2, 2019. \url{https://doi.org/10.2139/ssrn.3497001}.
		\item Biais, Bruno, Thierry Foucault, and Sophie Moinas. “Equilibrium Fast Trading.” Journal of Financial Economics 116, no. 2 (May 1, 2015): 292–313. \url{https://doi.org/10.1016/j.jfineco.2015.03.004}
		\item Budish, Eric, Peter Cramton, and John Shim. “The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response.” The Quarterly Journal of Economics 130, no. 4 (2015): 1547–1621. \url{https://doi.org/10.1093/qje/qjv027}
	\end{itemize}
	\item \textit{Week 13}: Public information; optimal disclosure policies; public announcements and trade volumes
	\begin{itemize}
		\item Kondor, Péter. “The More We Know about the Fundamental, the Less We Agree on the Price.” The Review of Economic Studies 79, no. 3 (2012): 1175–1207. \url{https://doi.org/10.1093/restud/rdr051}
	\end{itemize}
	\item \textit{Week 14}: Bubbles; herding; common knowledge
	\begin{itemize}
		%\item Smith, Lones, and Peter Sørensen. “Pathological Outcomes of Observational Learning.” Econometrica 68, no. 2 (2000): 371–398. \url{https://doi.org/10.1111/1468-0262.00113}
		\item Smith, Lones, and Peter Norman Sørensen. “Observational Learning.” The New Palgrave Dictionary of Economics Online Edition, 2011, 29–52. \url{http://www.econ.ku.dk/Sorensen/papers/observational-learning.pdf}
		\item Bikhchandani, Sushil, and Sunil Sharma. “Herd Behavior in Financial Markets.” IMF Staff Papers 47, no. 3 (2000): 279–310. \url{https://doi.org/10.2307/3867650}
		\item Abreu, Dilip, and Markus K. Brunnermeier. “Bubbles and Crashes.” Econometrica 71, no. 1 (2003): 173–204. \url{https://doi.org/10.1111/1468-0262.00393}
	\end{itemize}
	\item \textit{Week 15}: Auction models
	\begin{itemize}
		\item Krishna, Vijay. Auction theory (Chapters 2 and 6). Academic press, 2009. ISBN: 978-0-12-374507-1. \url{https://doi.org/10.1016/C2009-0-22474-3} 
	\end{itemize}
\end{itemize}

%\bigskip
%The list will be expanded and updated as we progress through the course.


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